000			03355nam a22005055i 4500
001			u372234
003			SIRSI
005			20160812084048.0
007			cr nn 008mamaa
008			110524s2011 xxu| s |||| 0|eng d
020			_a9781441994738 _9978-1-4419-9473-8
040			_cMX-MeUAM
050		4	_aQA273.A1-274.9
050		4	_aQA274-274.9
082	0	4	_a519.2 _223
100	1		_aFoss, Sergey. _eauthor.
245	1	3	_aAn Introduction to Heavy-Tailed and Subexponential Distributions _h[recurso electrónico] / _cby Sergey Foss, Dmitry Korshunov, Stan Zachary.
250			_a1.
264		1	_aNew York, NY : _bSpringer New York, _c2011.
300			_aIX, 123p. 1 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Operations Research and Financial Engineering, _x1431-8598 ; _v38
505	0		_aPreface -- Introduction -- Heavy- and long-tailed distributions -- Subexponential distributions.- Densities and local probabilities -- Maximum of random walks -- References -- Index.
520			_aHeavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions.  This monograph defines the classes of long-tailed and subexponential distributions in one dimension and provides a complete and comprehensive description of their properties. New results are presented in a simple, coherent and systematic way. This leads to a comprehensive exposition of tail properties of sums of independent random variables whose distributions belong to the long-tailed and subexponential class. The book includes a discussion of and references to contemporary areas of applications and also contains preliminary mathematical material which makes the book self contained. Modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.
650		0	_aMathematics.
650		0	_aDistribution (Probability theory).
650		0	_aEconomics _xStatistics.
650	1	4	_aMathematics.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aStatistics for Business/Economics/Mathematical Finance/Insurance.
650	2	4	_aStatistical Physics, Dynamical Systems and Complexity.
700	1		_aKorshunov, Dmitry. _eauthor.
700	1		_aZachary, Stan. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441994721
830		0	_aSpringer Series in Operations Research and Financial Engineering, _x1431-8598 ; _v38
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-4419-9473-8
596			_a19
942			_cLIBRO_ELEC
999			_c200114 _d200114